{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}D:\Asymmetric Loss Project\New Version (2012)\Data Folder\policy priorities.unrestricted reported models.pooled ols SCP model.07-15-2013.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}15 Jul 2013, 16:11:56
{txt}
{com}. 
. 
. 
. * OPEN "BASE 'PURSE STRINGS'" DATA SET
.   
. use "D:\Asymmetric Loss Project\New Version (2012)\Data Folder\policy priorities.02-01-12.dta", clear
{txt}
{com}.   
. 
.   
. 
. ****************************************************************************************************************************************
. ***************************************************************************************************************************************
. 
. ******* SCP MODEL: MODEL 1 (ROBUSTNESS CHECK OF UNRESTRICTED MODEL REPORTED IN MANUSCRIPT: SANS AGENCY-LEVEL AND TIME-WISE DUMMY FIXED EFFECTS IN SCP MODEL: BUT WITH SEs CLUSTER-ADJUSTED BY AGENCY) ********
. 
. 
. 
. ***************************************************************************************************************************************
. ***************************************************************************************************************************************
. ***************************************************************************************************************************************
. ***************************************************************************************************************************************
. 
. 
. 
. 
. **** FIRST-STAGE ESTIMATION: OBTAINING STATE-CONTINGENT PREFERENCE (SCP) PROPOSAL MODEL ESTIMATES *****
. 
. 
. set more off 
{txt}
{com}. 
. 
. xtset agencycode fiscalyear, yearly
{res}{txt}{col 8}panel variable:  {res}agencycode (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}fiscalyear, 1960 to 2009
{txt}{col 17}delta:  {res}1 year
{txt}
{com}. 
. * eststo clear
. 
. 
. 
. ** MODEL 1 (REPORTED IN THE MANUSCRIPT): (OMIT BOTH ASCIHA & ASCTHA INTERACTION TERMS FROM ACCOMMODATION PROPOSAL MODEL SPECIFICATION)
. 
. 
. regress prgrowth hdempct sdempct congelyr cpartmajchangecorrected asct asci lagbudgetgap ueratepres lagfedsurpdefpctgdp vietiraqwardefense budget74amends grh any_supp, vce(cluster agencycode)

{txt}Linear regression                                      Number of obs ={res}    1282
                                                       {help j_robustsingular:F( 12,    31) =}       .
                                                       {txt}Prob > F      = {res}      .
                                                       {txt}R-squared     = {res} 0.2242
                                                       {txt}Root MSE      = {res} 43.286

{txt}{ralign 89:(Std. Err. adjusted for {res:32} clusters in agencycode)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}               prgrowth{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}hdempct {c |}{col 25}{res}{space 2}-.5024583{col 37}{space 2} .4649601{col 48}{space 1}   -1.08{col 57}{space 3}0.288{col 65}{space 4}-1.450751{col 78}{space 3}  .445834
{txt}{space 16}sdempct {c |}{col 25}{res}{space 2}  1.03631{col 37}{space 2} .3607744{col 48}{space 1}    2.87{col 57}{space 3}0.007{col 65}{space 4} .3005061{col 78}{space 3} 1.772115
{txt}{space 15}congelyr {c |}{col 25}{res}{space 2} 6.340249{col 37}{space 2} 2.449027{col 48}{space 1}    2.59{col 57}{space 3}0.015{col 65}{space 4} 1.345426{col 78}{space 3} 11.33507
{txt}cpartmajchangecorrected {c |}{col 25}{res}{space 2}-3.220688{col 37}{space 2} 1.963298{col 48}{space 1}   -1.64{col 57}{space 3}0.111{col 65}{space 4}-7.224861{col 78}{space 3} .7834858
{txt}{space 19}asct {c |}{col 25}{res}{space 2}-.0411549{col 37}{space 2} .3005397{col 48}{space 1}   -0.14{col 57}{space 3}0.892{col 65}{space 4}-.6541097{col 78}{space 3} .5717999
{txt}{space 19}asci {c |}{col 25}{res}{space 2}-.4785653{col 37}{space 2} 3.509414{col 48}{space 1}   -0.14{col 57}{space 3}0.892{col 65}{space 4}-7.636063{col 78}{space 3} 6.678932
{txt}{space 11}lagbudgetgap {c |}{col 25}{res}{space 2} .3670786{col 37}{space 2}  .069464{col 48}{space 1}    5.28{col 57}{space 3}0.000{col 65}{space 4} .2254058{col 78}{space 3} .5087513
{txt}{space 13}ueratepres {c |}{col 25}{res}{space 2} 2.069561{col 37}{space 2} 2.059875{col 48}{space 1}    1.00{col 57}{space 3}0.323{col 65}{space 4}-2.131582{col 78}{space 3} 6.270704
{txt}{space 4}lagfedsurpdefpctgdp {c |}{col 25}{res}{space 2} 2.434718{col 37}{space 2} 1.049109{col 48}{space 1}    2.32{col 57}{space 3}0.027{col 65}{space 4} .2950459{col 78}{space 3} 4.574389
{txt}{space 5}vietiraqwardefense {c |}{col 25}{res}{space 2} -3.48879{col 37}{space 2} 2.549091{col 48}{space 1}   -1.37{col 57}{space 3}0.181{col 65}{space 4}-8.687696{col 78}{space 3} 1.710116
{txt}{space 9}budget74amends {c |}{col 25}{res}{space 2} 3.160464{col 37}{space 2}  2.56031{col 48}{space 1}    1.23{col 57}{space 3}0.226{col 65}{space 4}-2.061323{col 78}{space 3} 8.382251
{txt}{space 20}grh {c |}{col 25}{res}{space 2}-1.375209{col 37}{space 2} 3.301012{col 48}{space 1}   -0.42{col 57}{space 3}0.680{col 65}{space 4}-8.107667{col 78}{space 3} 5.357248
{txt}{space 15}any_supp {c |}{col 25}{res}{space 2}-4.543926{col 37}{space 2} 2.890832{col 48}{space 1}   -1.57{col 57}{space 3}0.126{col 65}{space 4}-10.43982{col 78}{space 3} 1.351964
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-36.17538{col 37}{space 2} 11.47663{col 48}{space 1}   -3.15{col 57}{space 3}0.004{col 65}{space 4}-59.58212{col 78}{space 3}-12.76863
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 
.                 
. 
. * OBTAIN THE STATE-CONTINGENT PREFERENCE (SCP) PROPOSAL BY COMPUTING THE PREDICTED VALUES OF THE DEPENDENT VARIABLE
. 
. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1282{col 25}-6805.073{col 37}-6642.384{col 48}   13{col 57} 13310.77{col 69}  13377.8
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. 
. predict scpprop, xb
{txt}(312 missing values generated)

{com}. 
. 
. 
. 
. ***************************************************************************************************************************************
. 
. ***************************************************************************************************************************************
. 
. ***************************************************************************************************************************************
. 
. 
. **** SECOND-STAGE ESTIMATION: OBTAINING GENERALIZED PROPOSAL (GP) MODEL ESTIMATES *****
. 
. 
. 
. 
. **** EQUATION (2.1): EXCESS FUNDINGS BIAS EQUATION ANALYSIS *****
. 
. 
. * The xtset needs to be cleared in order to make the bootstrap process work with the cluster() and idcluster()
. 
. xtset, clear
{txt}
{com}. bootstrap _b, reps(10008) bca seed(123) nodots cluster(agencycode) idcluster(newagencycode): regress prgrowth scpprop presparty libagency modagency partymod partylib
{res}
{txt}Linear regression{col 49}Number of obs{col 68}= {res}     1282
{txt}{col 49}Replications{col 68}= {res}    10000
{txt}{col 49}Wald chi2({res}6{txt}){col 68}= {res}    58.38
{txt}{col 49}Prob > chi2{col 68}= {res}   0.0000
{txt}{col 49}R-squared{col 68}= {res}   0.2277
{txt}{col 49}Adj R-squared{col 68}= {res}   0.2240
{txt}{col 49}Root MSE{col 68}= {res}  43.0687

{txt}{ralign 78:(Replications based on {res:32} clusters in agencycode)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}   Observed{col 26}   Bootstrap{col 54}         Norm{col 67}al-based
{col 1}    prgrowth{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}scpprop {c |}{col 14}{res}{space 2} 1.018453{col 26}{space 2} .1859348{col 37}{space 1}    5.48{col 46}{space 3}0.000{col 54}{space 4} .6540279{col 67}{space 3} 1.382879
{txt}{space 3}presparty {c |}{col 14}{res}{space 2} 1.239602{col 26}{space 2} 3.726999{col 37}{space 1}    0.33{col 46}{space 3}0.739{col 54}{space 4}-6.065183{col 67}{space 3} 8.544386
{txt}{space 3}libagency {c |}{col 14}{res}{space 2} 4.406754{col 26}{space 2} 5.528432{col 37}{space 1}    0.80{col 46}{space 3}0.425{col 54}{space 4}-6.428774{col 67}{space 3} 15.24228
{txt}{space 3}modagency {c |}{col 14}{res}{space 2}-1.863535{col 26}{space 2} 3.392607{col 37}{space 1}   -0.55{col 46}{space 3}0.583{col 54}{space 4}-8.512923{col 67}{space 3} 4.785853
{txt}{space 4}partymod {c |}{col 14}{res}{space 2}-4.852137{col 26}{space 2} 4.394444{col 37}{space 1}   -1.10{col 46}{space 3}0.270{col 54}{space 4}-13.46509{col 67}{space 3} 3.760816
{txt}{space 4}partylib {c |}{col 14}{res}{space 2}-3.610677{col 26}{space 2} 6.623092{col 37}{space 1}   -0.55{col 46}{space 3}0.586{col 54}{space 4} -16.5917{col 67}{space 3} 9.370344
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.0426541{col 26}{space 2} 2.710008{col 37}{space 1}   -0.02{col 46}{space 3}0.987{col 54}{space 4}-5.354173{col 67}{space 3} 5.268865
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 79}Note: one or more parameters could not be estimated in 8 bootstrap replicates; standard-error estimates include only complete replications.{p_end}

{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1282{col 25}-6805.073{col 37}-6639.475{col 48}    7{col 57} 13292.95{col 69} 13329.04
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. predict bstrapeq2, xb
{txt}(312 missing values generated)

{com}. 
. xtile bootmedcons1=_b[_cons], nquantiles(2)
{txt}
{com}. xtile bootmedscpprop=_b[scpprop], nquantiles(2)
{txt}
{com}. xtile bootmedparty=_b[presparty], nquantiles(2)
{txt}
{com}. xtile bootmedlibagency=_b[libagency], nquantiles(2)
{txt}
{com}. xtile bootmedmodagency=_b[modagency], nquantiles(2)
{txt}
{com}. xtile bootmedpartymod=_b[partymod], nquantiles(2)
{txt}
{com}. xtile bootmedpartylib=_b[partylib], nquantiles(2)
{txt}
{com}. 
. 
. * Now we have to Reset the Panel Data Declaration
. 
. xtset agencycode fiscalyear, yearly
{res}{txt}{col 8}panel variable:  {res}agencycode (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}fiscalyear, 1960 to 2009
{txt}{col 17}delta:  {res}1 year
{txt}
{com}. 
. 
. * Generating Predicted Values of the Observed Proposal (OP)
. 
. gen predreq1=bootmedcons1+bootmedscpprop*scpprop+bootmedparty*presparty+bootmedlibagency*libagency+bootmedmodagency*modagency+bootmedpartymod*partymod+bootmedpartylib*partylib
{txt}(312 missing values generated)

{com}. 
. 
. * Generating the Residuals from Stage 1
. 
. gen residstage1=prgrowth-predreq1
{txt}(318 missing values generated)

{com}. gen absresidstage1=abs(residstage1)
{txt}(318 missing values generated)

{com}. 
. 
. 
. *************************************************************************************************************************************
. * EQUATION (2.2) -- FIRST-STAGE ARCH(j) MODEL ESTIMATES: j=1, j=2, j=3, & j=4 (ANALYSIS FROM 1 TO 4 LAGS ON THE ARCH TERMS) *
. *************************************************************************************************************************************
. 
. xtreg absresidstage1 l.absresidstage1, fe

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1241
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.1430                         {txt}Obs per group: min = {res}       17
{txt}       between = {res}0.9923                                        {txt}avg = {res}     38.8
{txt}       overall = {res}0.2165                                        {txt}max = {res}       46

                                                {txt}F({res}1{txt},{res}1208{txt})          = {res}   201.59
{txt}corr(u_i, Xb)  = {res}0.3736                         {txt}Prob > F           =    {res}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}absresidstage1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
absresidstage1 {c |}
{space 11}L1. {c |}{col 16}{res}{space 2} .3654695{col 28}{space 2} .0257405{col 39}{space 1}   14.20{col 48}{space 3}0.000{col 56}{space 4} .3149685{col 69}{space 3} .4159705
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} 11.74014{col 28}{space 2} 1.056727{col 39}{space 1}   11.11{col 48}{space 3}0.000{col 56}{space 4} 9.666917{col 69}{space 3} 13.81337
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       sigma_u {c |} {res}  8.788192
       {txt}sigma_e {c |} {res} 32.612739
           {txt}rho {c |} {res} .06769877{txt}   (fraction of variance due to u_i)
{hline 15}{c BT}{hline 64}
F test that all u_i=0:     F({res}31{txt}, {res}1208{txt}) = {res}    2.44            {txt}Prob > F = {res}0.0000
{txt}
{com}. predict absresid1stpred1, xbu
{txt}(359 missing values generated)

{com}. estat ic 

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1241{col 25}-6164.459{col 37}-6068.696{col 48}    2{col 57} 12141.39{col 69} 12151.64
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. *
. 
. xtreg absresidstage1 l(1/2).absresidstage1, fe

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1202
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.1595                         {txt}Obs per group: min = {res}       16
{txt}       between = {res}0.9962                                        {txt}avg = {res}     37.6
{txt}       overall = {res}0.2422                                        {txt}max = {res}       45

                                                {txt}F({res}2{txt},{res}1168{txt})          = {res}   110.80
{txt}corr(u_i, Xb)  = {res}0.4088                         {txt}Prob > F           =    {res}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}absresidstage1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
absresidstage1 {c |}
{space 11}L1. {c |}{col 16}{res}{space 2} .3560838{col 28}{space 2} .0289051{col 39}{space 1}   12.32{col 48}{space 3}0.000{col 56}{space 4} .2993721{col 69}{space 3} .4127954
{txt}{space 11}L2. {c |}{col 16}{res}{space 2} .0859975{col 28}{space 2} .0282386{col 39}{space 1}    3.05{col 48}{space 3}0.002{col 56}{space 4} .0305935{col 69}{space 3} .1414016
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2}  10.4253{col 28}{space 2} 1.126386{col 39}{space 1}    9.26{col 48}{space 3}0.000{col 56}{space 4} 8.215335{col 69}{space 3} 12.63527
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       sigma_u {c |} {res} 8.1872542
       {txt}sigma_e {c |} {res} 32.596294
           {txt}rho {c |} {res} .05934324{txt}   (fraction of variance due to u_i)
{hline 15}{c BT}{hline 64}
F test that all u_i=0:     F({res}31{txt}, {res}1168{txt}) = {res}    1.89            {txt}Prob > F = {res}0.0023
{txt}
{com}. predict absresid1stpred2, xbu
{txt}(398 missing values generated)

{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1202{col 25}-5980.731{col 37}-5876.326{col 48}    3{col 57} 11758.65{col 69} 11773.93
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. *
. 
. xtreg absresidstage1 l(1/3).absresidstage1, fe

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1163
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.1654                         {txt}Obs per group: min = {res}       15
{txt}       between = {res}0.9936                                        {txt}avg = {res}     36.3
{txt}       overall = {res}0.2416                                        {txt}max = {res}       44

                                                {txt}F({res}3{txt},{res}1128{txt})          = {res}    74.49
{txt}corr(u_i, Xb)  = {res}0.3883                         {txt}Prob > F           =    {res}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}absresidstage1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
absresidstage1 {c |}
{space 11}L1. {c |}{col 16}{res}{space 2} .3767409{col 28}{space 2} .0290118{col 39}{space 1}   12.99{col 48}{space 3}0.000{col 56}{space 4} .3198177{col 69}{space 3} .4336641
{txt}{space 11}L2. {c |}{col 16}{res}{space 2} .0526052{col 28}{space 2} .0307394{col 39}{space 1}    1.71{col 48}{space 3}0.087{col 56}{space 4}-.0077075{col 69}{space 3}  .112918
{txt}{space 11}L3. {c |}{col 16}{res}{space 2} -.011588{col 28}{space 2} .0280233{col 39}{space 1}   -0.41{col 48}{space 3}0.679{col 56}{space 4}-.0665718{col 69}{space 3} .0433957
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} 10.62381{col 28}{space 2} 1.169942{col 39}{space 1}    9.08{col 48}{space 3}0.000{col 56}{space 4} 8.328307{col 69}{space 3} 12.91932
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       sigma_u {c |} {res} 8.0013639
       {txt}sigma_e {c |} {res} 32.148053
           {txt}rho {c |} {res} .05833322{txt}   (fraction of variance due to u_i)
{hline 15}{c BT}{hline 64}
F test that all u_i=0:     F({res}31{txt}, {res}1128{txt}) = {res}    1.66            {txt}Prob > F = {res}0.0136
{txt}
{com}. predict absresid1stpred3, xbu
{txt}(437 missing values generated)

{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1163{col 25}-5773.586{col 37}-5668.476{col 48}    4{col 57} 11344.95{col 69} 11365.19
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. *
. 
. xtreg absresidstage1 l(1/4).absresidstage1, fe

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1124
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.1829                         {txt}Obs per group: min = {res}       14
{txt}       between = {res}0.9782                                        {txt}avg = {res}     35.1
{txt}       overall = {res}0.2532                                        {txt}max = {res}       43

                                                {txt}F({res}4{txt},{res}1088{txt})          = {res}    60.87
{txt}corr(u_i, Xb)  = {res}0.3639                         {txt}Prob > F           =    {res}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}absresidstage1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
absresidstage1 {c |}
{space 11}L1. {c |}{col 16}{res}{space 2} .3808959{col 28}{space 2} .0285166{col 39}{space 1}   13.36{col 48}{space 3}0.000{col 56}{space 4} .3249422{col 69}{space 3} .4368496
{txt}{space 11}L2. {c |}{col 16}{res}{space 2} .0598132{col 28}{space 2} .0300516{col 39}{space 1}    1.99{col 48}{space 3}0.047{col 56}{space 4} .0008476{col 69}{space 3} .1187788
{txt}{space 11}L3. {c |}{col 16}{res}{space 2}-.0069945{col 28}{space 2} .0294016{col 39}{space 1}   -0.24{col 48}{space 3}0.812{col 56}{space 4}-.0646848{col 69}{space 3} .0506958
{txt}{space 11}L4. {c |}{col 16}{res}{space 2}-.0170815{col 28}{space 2} .0270005{col 39}{space 1}   -0.63{col 48}{space 3}0.527{col 56}{space 4}-.0700604{col 69}{space 3} .0358975
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} 10.31478{col 28}{space 2} 1.171293{col 39}{space 1}    8.81{col 48}{space 3}0.000{col 56}{space 4} 8.016526{col 69}{space 3} 12.61303
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       sigma_u {c |} {res} 7.3933623
       {txt}sigma_e {c |} {res}   30.6055
           {txt}rho {c |} {res} .05513829{txt}   (fraction of variance due to u_i)
{hline 15}{c BT}{hline 64}
F test that all u_i=0:     F({res}31{txt}, {res}1088{txt}) = {res}    1.46            {txt}Prob > F = {res}0.0499
{txt}
{com}. predict absresid1stpred4, xbu
{txt}(476 missing values generated)

{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1124{col 25}-5535.498{col 37}-5421.998{col 48}    5{col 57}    10854{col 69} 10879.12
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. *
. 
. 
. 
. correlate absresid1stpred1 absresid1stpred2 absresid1stpred3 absresid1stpred4 
{txt}(obs=1124)

             {c |} absre~d1 absres~2 absres~3 absres~4
{hline 13}{c +}{hline 36}
absresid1s~1 {c |}{res}   1.0000
{txt}absresid1s~2 {c |}{res}   0.9895   1.0000
{txt}absresid1s~3 {c |}{res}   0.9938   0.9957   1.0000
{txt}absresid1s~4 {c |}{res}   0.9870   0.9916   0.9950   1.0000

{txt}
{com}. 
. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. * BASE SUBSEQUENT ANALYSIS ON ARCH(1)RESIDUAL PROCESS OBTAINED IN EQUATION (2.2) SINCE IT IS BEST FIT TO DATA AND HIGHLY CORRELATED WITH HIGHER-ORDER ARCH PROCESSES *
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. 
. *The result from the above list of procedures is that we will use a single lag for the model to bootstrap
. 
. * Bootstrapped ARCH model using the asbsolute values of the residuals from the preceding procedure *
. 
. xtset agencycode fiscalyear, yearly
{res}{txt}{col 8}panel variable:  {res}agencycode (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}fiscalyear, 1960 to 2009
{txt}{col 17}delta:  {res}1 year
{txt}
{com}. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. * EQUATION (2.3): ESTIMATE "FINAL" FIRST-STAGE ARCH(1) RESIDUAL ANALYSIS *
. ************************************************************************************************************************************************************************************************************************************** 
. 
. gen lagabsresidstage1=l.absresidstage1
{txt}(343 missing values generated)

{com}. bootstrap _b, reps(10003) bca seed(123) nodots saving(eq3boot, replace): xtreg absresidstage1 lagabsresidstage1, fe
{res}
{txt}Fixed-effects (within) regression               Number of obs      = {res}     1241
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.1430                         {txt}Obs per group: min = {res}       17
{txt}       between = {res}0.9923                                        {txt}avg = {res}     38.8
{txt}       overall = {res}0.2165                                        {txt}max = {res}       46

                                                {txt}Wald chi2({res}1{txt})       = {res}    25.59
{txt}corr(u_i, Xb)  = {res}0.3736                         {txt}Prob > chi2        =    {res}0.0000

{txt}{ralign 83:(Replications based on clustering on agencycode)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}   Observed{col 31}   Bootstrap{col 59}         Norm{col 72}al-based
{col 1}   absresidstage1{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
lagabsresidstage1 {c |}{col 19}{res}{space 2} .3654695{col 31}{space 2} .0722433{col 42}{space 1}    5.06{col 51}{space 3}0.000{col 59}{space 4} .2238752{col 72}{space 3} .5070638
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} 11.74014{col 31}{space 2} 1.480459{col 42}{space 1}    7.93{col 51}{space 3}0.000{col 59}{space 4} 8.838495{col 72}{space 3} 14.64179
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          sigma_u {c |} {res}  8.788192
          {txt}sigma_e {c |} {res} 32.612739
              {txt}rho {c |} {res} .06769877{txt}   (fraction of variance due to u_i)
{hline 18}{c BT}{hline 64}

{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1241{col 25}-6164.459{col 37}-6068.696{col 48}    2{col 57} 12141.39{col 69} 12151.64
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. predict bstrapeq3, xbu
{txt}(359 missing values generated)

{com}. 
. xtile bootmedcons2=_b[_cons], nquantiles(2)
{txt}
{com}. xtile bootmedlagabsresid2=_b[lagabsresidstage1], nquantiles(2)
{txt}
{com}. 
. gen cfesdhat1=bootmedcons2+bootmedlagabsresid2*lagabsresidstage1
{txt}(343 missing values generated)

{com}.  
. gen cfesd1party=cfesdhat1*presparty
{txt}(343 missing values generated)

{com}. gen cfesd1modagency=cfesdhat1*modagency
{txt}(343 missing values generated)

{com}. gen cfesd1libagency=cfesdhat1*libagency
{txt}(343 missing values generated)

{com}. gen cfesd1partymodag=cfesdhat1*modagency*presparty
{txt}(343 missing values generated)

{com}. gen cfesd1partylibag=cfesdhat1*libagency*presparty
{txt}(343 missing values generated)

{com}. 
. regress prgrowth scpprop presparty libagency modagency partymod partylib ///
>         cfesdhat1 cfesd1party cfesd1modagency cfesd1libagency cfesd1partymodag cfesd1partylibag

      {txt}Source {c |}       SS       df       MS              Number of obs ={res}    1241
{txt}{hline 13}{char +}{hline 30}           F( 12,  1228) ={res}   20.83
    {txt}   Model {char |} {res} 426374.095    12  35531.1746           {txt}Prob > F      = {res} 0.0000
    {txt}Residual {char |} {res} 2094564.02  1228  1705.67103           {txt}R-squared     = {res} 0.1691
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.1610
    {txt}   Total {char |} {res} 2520938.12  1240  2033.01461           {txt}Root MSE      = {res}   41.3

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        prgrowth{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}scpprop {c |}{col 18}{res}{space 2} .8441316{col 30}{space 2} .0617584{col 41}{space 1}   13.67{col 50}{space 3}0.000{col 58}{space 4} .7229679{col 71}{space 3} .9652952
{txt}{space 7}presparty {c |}{col 18}{res}{space 2}-.3216587{col 30}{space 2} 5.149692{col 41}{space 1}   -0.06{col 50}{space 3}0.950{col 58}{space 4}-10.42483{col 71}{space 3} 9.781511
{txt}{space 7}libagency {c |}{col 18}{res}{space 2}-4.456081{col 30}{space 2} 3.921029{col 41}{space 1}   -1.14{col 50}{space 3}0.256{col 58}{space 4}-12.14874{col 71}{space 3} 3.236578
{txt}{space 7}modagency {c |}{col 18}{res}{space 2}-4.144789{col 30}{space 2} 3.883889{col 41}{space 1}   -1.07{col 50}{space 3}0.286{col 58}{space 4}-11.76458{col 71}{space 3} 3.475003
{txt}{space 8}partymod {c |}{col 18}{res}{space 2}-10.21577{col 30}{space 2} 7.200544{col 41}{space 1}   -1.42{col 50}{space 3}0.156{col 58}{space 4} -24.3425{col 71}{space 3}  3.91096
{txt}{space 8}partylib {c |}{col 18}{res}{space 2}-6.574868{col 30}{space 2} 8.430567{col 41}{space 1}   -0.78{col 50}{space 3}0.436{col 58}{space 4}-23.11478{col 71}{space 3} 9.965043
{txt}{space 7}cfesdhat1 {c |}{col 18}{res}{space 2}-.1621447{col 30}{space 2} .0461597{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4}-.2527052{col 71}{space 3}-.0715842
{txt}{space 5}cfesd1party {c |}{col 18}{res}{space 2}  .125116{col 30}{space 2} .1753019{col 41}{space 1}    0.71{col 50}{space 3}0.476{col 58}{space 4}-.2188084{col 71}{space 3} .4690404
{txt}{space 1}cfesd1modagency {c |}{col 18}{res}{space 2} .1040152{col 30}{space 2} .1329304{col 41}{space 1}    0.78{col 50}{space 3}0.434{col 58}{space 4}-.1567807{col 71}{space 3} .3648111
{txt}{space 1}cfesd1libagency {c |}{col 18}{res}{space 2} .3083494{col 30}{space 2}  .067696{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .1755369{col 71}{space 3} .4411619
{txt}cfesd1partymodag {c |}{col 18}{res}{space 2} .1872754{col 30}{space 2}  .242316{col 41}{space 1}    0.77{col 50}{space 3}0.440{col 58}{space 4}-.2881239{col 71}{space 3} .6626746
{txt}cfesd1partylibag {c |}{col 18}{res}{space 2} .3909586{col 30}{space 2}  .287033{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.1721709{col 71}{space 3}  .954088
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.392891{col 30}{space 2}  2.41856{col 41}{space 1}    1.40{col 50}{space 3}0.161{col 58}{space 4}-1.352076{col 71}{space 3} 8.137858
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. * EQUATION (2.4): FIRST-STAGE GENERALIZED PROPOSAL MODEL ESTIMATES *
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. xtset, clear
{txt}
{com}. 
. bootstrap _b, reps(10010) bca seed(123) nodots cluster(agencycode) idcluster(new2agencycode) saving(cfesregboot, replace): ///
>         regress prgrowth scpprop presparty libagency modagency partymod partylib cfesdhat1 cfesd1party ///
>         cfesd1modagency cfesd1libagency cfesd1partymodag cfesd1partylibag
{res}
{txt}Linear regression{col 49}Number of obs{col 68}= {res}     1241
{txt}{col 49}Replications{col 68}= {res}    10000
{txt}{col 49}Wald chi2({res}12{txt}){col 68}= {res}    45.20
{txt}{col 49}Prob > chi2{col 68}= {res}   0.0000
{txt}{col 49}R-squared{col 68}= {res}   0.1691
{txt}{col 49}Adj R-squared{col 68}= {res}   0.1610
{txt}{col 49}Root MSE{col 68}= {res}  41.2998

{txt}{ralign 82:(Replications based on {res:32} clusters in agencycode)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}   Observed{col 30}   Bootstrap{col 58}         Norm{col 71}al-based
{col 1}        prgrowth{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}scpprop {c |}{col 18}{res}{space 2} .8441316{col 30}{space 2} .2378363{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4}  .377981{col 71}{space 3} 1.310282
{txt}{space 7}presparty {c |}{col 18}{res}{space 2}-.3216587{col 30}{space 2} 6.121866{col 41}{space 1}   -0.05{col 50}{space 3}0.958{col 58}{space 4} -12.3203{col 71}{space 3} 11.67698
{txt}{space 7}libagency {c |}{col 18}{res}{space 2}-4.456081{col 30}{space 2} 5.946094{col 41}{space 1}   -0.75{col 50}{space 3}0.454{col 58}{space 4}-16.11021{col 71}{space 3}  7.19805
{txt}{space 7}modagency {c |}{col 18}{res}{space 2}-4.144789{col 30}{space 2}  4.93082{col 41}{space 1}   -0.84{col 50}{space 3}0.401{col 58}{space 4}-13.80902{col 71}{space 3}  5.51944
{txt}{space 8}partymod {c |}{col 18}{res}{space 2}-10.21577{col 30}{space 2}  6.84882{col 41}{space 1}   -1.49{col 50}{space 3}0.136{col 58}{space 4}-23.63921{col 71}{space 3}  3.20767
{txt}{space 8}partylib {c |}{col 18}{res}{space 2}-6.574868{col 30}{space 2} 10.74048{col 41}{space 1}   -0.61{col 50}{space 3}0.540{col 58}{space 4}-27.62583{col 71}{space 3} 14.47609
{txt}{space 7}cfesdhat1 {c |}{col 18}{res}{space 2}-.1621447{col 30}{space 2} .1386334{col 41}{space 1}   -1.17{col 50}{space 3}0.242{col 58}{space 4}-.4338612{col 71}{space 3} .1095718
{txt}{space 5}cfesd1party {c |}{col 18}{res}{space 2}  .125116{col 30}{space 2} .2472816{col 41}{space 1}    0.51{col 50}{space 3}0.613{col 58}{space 4}-.3595471{col 71}{space 3} .6097791
{txt}{space 1}cfesd1modagency {c |}{col 18}{res}{space 2} .1040152{col 30}{space 2} .1723017{col 41}{space 1}    0.60{col 50}{space 3}0.546{col 58}{space 4}-.2336899{col 71}{space 3} .4417204
{txt}{space 1}cfesd1libagency {c |}{col 18}{res}{space 2} .3083494{col 30}{space 2} .1638691{col 41}{space 1}    1.88{col 50}{space 3}0.060{col 58}{space 4}-.0128281{col 71}{space 3} .6295269
{txt}cfesd1partymodag {c |}{col 18}{res}{space 2} .1872754{col 30}{space 2} .2965891{col 41}{space 1}    0.63{col 50}{space 3}0.528{col 58}{space 4}-.3940286{col 71}{space 3} .7685793
{txt}cfesd1partylibag {c |}{col 18}{res}{space 2} .3909586{col 30}{space 2} .5127949{col 41}{space 1}    0.76{col 50}{space 3}0.446{col 58}{space 4} -.614101{col 71}{space 3} 1.396018
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.392891{col 30}{space 2} 4.672782{col 41}{space 1}    0.73{col 50}{space 3}0.468{col 58}{space 4}-5.765594{col 71}{space 3} 12.55138
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 79}Note: one or more parameters could not be estimated in 10 bootstrap replicates; standard-error estimates include only complete replications.{p_end}

{com}. 
.     estat ic 

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1241{col 25}-6486.922{col 37}-6371.952{col 48}   13{col 57}  12769.9{col 69} 12836.51
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}.         
.         predict bstrapeq4, xb
{txt}(357 missing values generated)

{com}. 
. xtile bootmedcons3=_b[_cons], nquantiles(2)
{txt}
{com}. xtile bootmedscpprop3=_b[scpprop], nquantiles(2)
{txt}
{com}. xtile bootmedparty3=_b[presparty], nquantiles(2) 
{txt}
{com}. xtile bootmedlibagency3=_b[libagency], nquantiles(2)
{txt}
{com}. xtile bootmedmodagency3=_b[modagency], nquantiles(2)
{txt}
{com}. xtile bootmedpartymod3=_b[partymod], nquantiles(2)
{txt}
{com}. xtile bootmedpartylib3=_b[partylib], nquantiles(2)
{txt}
{com}. xtile bootmedcfesd3=_b[cfesdhat1],  nquantiles(2)
{txt}
{com}. xtile bootmedcfesdparty3=_b[cfesd1party],  nquantiles(2)
{txt}
{com}. xtile bootmedcfesdma3=_b[cfesd1modagency],  nquantiles(2)
{txt}
{com}. xtile bootmedcfesdla3=_b[cfesd1libagency],  nquantiles(2)
{txt}
{com}. xtile bootmedcfesdpma3=_b[cfesd1partymodag],  nquantiles(2)
{txt}
{com}. xtile bootmedcfesdpla3=_b[cfesd1partylibag], nquantiles(2)
{txt}
{com}. 
. xtset agencycode fiscalyear, yearly
{res}{txt}{col 8}panel variable:  {res}agencycode (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}fiscalyear, 1960 to 2009
{txt}{col 17}delta:  {res}1 year
{txt}
{com}. 
. generate predvalstage2= bootmedcons3 + bootmedparty3*presparty + bootmedscpprop3*scpprop + ///
>         bootmedlibagency3*libagency + bootmedmodagency3*modagency + bootmedpartymod3*partymod + bootmedpartylib3*partylib + ///
>         bootmedcfesd3*cfesdhat1+ bootmedcfesdparty3*cfesd1party + bootmedcfesdma3*cfesd1modagency + ///
>         bootmedcfesdla3*cfesd1libagency + bootmedcfesdpma3*cfesd1partymodag + bootmedcfesdpla3*cfesd1partylibag
{txt}(357 missing values generated)

{com}. 
.         
. *generate residuals and absolute residuals from the prior procedures 
. 
. gen residstage2 = prgrowth-predvalstage2
{txt}(359 missing values generated)

{com}. 
. gen absresidstage2 = abs(residstage2)
{txt}(359 missing values generated)

{com}. 
. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. * Testing the Residual Process from SECOND-STAGE ARCH(j) Analysis (ANALYSIS FROM 1 TO 4 LAGS ON THE ARCH TERMS) *
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. xtreg absresidstage2 l(1/1).absresidstage2, fe

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1202
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.2387                         {txt}Obs per group: min = {res}       16
{txt}       between = {res}0.9886                                        {txt}avg = {res}     37.6
{txt}       overall = {res}0.3221                                        {txt}max = {res}       45

                                                {txt}F({res}1{txt},{res}1169{txt})          = {res}   366.58
{txt}corr(u_i, Xb)  = {res}0.3875                         {txt}Prob > F           =    {res}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}absresidstage2{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
absresidstage2 {c |}
{space 11}L1. {c |}{col 16}{res}{space 2} .4725866{col 28}{space 2}  .024683{col 39}{space 1}   19.15{col 48}{space 3}0.000{col 56}{space 4} .4241587{col 69}{space 3} .5210145
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} 24.25309{col 28}{space 2} 2.278973{col 39}{space 1}   10.64{col 48}{space 3}0.000{col 56}{space 4} 19.78176{col 69}{space 3} 28.72443
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       sigma_u {c |} {res} 17.716771
       {txt}sigma_e {c |} {res} 66.737115
           {txt}rho {c |} {res} .06583515{txt}   (fraction of variance due to u_i)
{hline 15}{c BT}{hline 64}
F test that all u_i=0:     F({res}31{txt}, {res}1169{txt}) = {res}    2.03            {txt}Prob > F = {res}0.0007
{txt}
{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1202{col 25}-6902.077{col 37}-6738.148{col 48}    2{col 57}  13480.3{col 69} 13490.48
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. predict absresid2ndpred1, xbu
{txt}(398 missing values generated)

{com}. *
. 
. xtreg absresidstage2 l(1/2).absresidstage2, fe

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1163
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.2489                         {txt}Obs per group: min = {res}       15
{txt}       between = {res}0.9952                                        {txt}avg = {res}     36.3
{txt}       overall = {res}0.3334                                        {txt}max = {res}       44

                                                {txt}F({res}2{txt},{res}1129{txt})          = {res}   187.05
{txt}corr(u_i, Xb)  = {res}0.3944                         {txt}Prob > F           =    {res}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}absresidstage2{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
absresidstage2 {c |}
{space 11}L1. {c |}{col 16}{res}{space 2} .5006618{col 28}{space 2} .0292925{col 39}{space 1}   17.09{col 48}{space 3}0.000{col 56}{space 4}  .443188{col 69}{space 3} .5581356
{txt}{space 11}L2. {c |}{col 16}{res}{space 2}-.0101034{col 28}{space 2} .0282187{col 39}{space 1}   -0.36{col 48}{space 3}0.720{col 56}{space 4}-.0654704{col 69}{space 3} .0452637
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} 23.57214{col 28}{space 2} 2.417903{col 39}{space 1}    9.75{col 48}{space 3}0.000{col 56}{space 4} 18.82805{col 69}{space 3} 28.31623
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       sigma_u {c |} {res}  17.58113
       {txt}sigma_e {c |} {res} 66.415819
           {txt}rho {c |} {res} .06548429{txt}   (fraction of variance due to u_i)
{hline 15}{c BT}{hline 64}
F test that all u_i=0:     F({res}31{txt}, {res}1129{txt}) = {res}    1.79            {txt}Prob > F = {res}0.0052
{txt}
{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1163{col 25}-6679.266{col 37}-6512.845{col 48}    3{col 57} 13031.69{col 69} 13046.87
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. predict absresid2ndpred2, xbu
{txt}(437 missing values generated)

{com}. *
. 
. xtreg absresidstage2 l(1/3).absresidstage2, fe

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1124
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.2591                         {txt}Obs per group: min = {res}       14
{txt}       between = {res}0.9929                                        {txt}avg = {res}     35.1
{txt}       overall = {res}0.3445                                        {txt}max = {res}       43

                                                {txt}F({res}3{txt},{res}1089{txt})          = {res}   126.94
{txt}corr(u_i, Xb)  = {res}0.4033                         {txt}Prob > F           =    {res}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}absresidstage2{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
absresidstage2 {c |}
{space 11}L1. {c |}{col 16}{res}{space 2} .5108636{col 28}{space 2} .0299355{col 39}{space 1}   17.07{col 48}{space 3}0.000{col 56}{space 4} .4521258{col 69}{space 3} .5696014
{txt}{space 11}L2. {c |}{col 16}{res}{space 2} -.020958{col 28}{space 2} .0330211{col 39}{space 1}   -0.63{col 48}{space 3}0.526{col 56}{space 4}-.0857502{col 69}{space 3} .0438342
{txt}{space 11}L3. {c |}{col 16}{res}{space 2} .0272348{col 28}{space 2} .0285877{col 39}{space 1}    0.95{col 48}{space 3}0.341{col 56}{space 4}-.0288585{col 69}{space 3} .0833281
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2}  21.6739{col 28}{space 2} 2.554807{col 39}{space 1}    8.48{col 48}{space 3}0.000{col 56}{space 4}   16.661{col 69}{space 3}  26.6868
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       sigma_u {c |} {res} 16.279653
       {txt}sigma_e {c |} {res} 66.365921
           {txt}rho {c |} {res} .05675752{txt}   (fraction of variance due to u_i)
{hline 15}{c BT}{hline 64}
F test that all u_i=0:     F({res}31{txt}, {res}1089{txt}) = {res}    1.41            {txt}Prob > F = {res}0.0692
{txt}
{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1124{col 25} -6461.03{col 37}-6292.495{col 48}    4{col 57} 12592.99{col 69} 12613.09
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. predict absresid2ndpred3, xbu
{txt}(476 missing values generated)

{com}. *
. 
. xtreg absresidstage2 l(1/4).absresidstage2, fe

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1085
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.2753                         {txt}Obs per group: min = {res}       13
{txt}       between = {res}0.9824                                        {txt}avg = {res}     33.9
{txt}       overall = {res}0.3494                                        {txt}max = {res}       42

                                                {txt}F({res}4{txt},{res}1049{txt})          = {res}    99.65
{txt}corr(u_i, Xb)  = {res}0.3487                         {txt}Prob > F           =    {res}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}absresidstage2{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
absresidstage2 {c |}
{space 11}L1. {c |}{col 16}{res}{space 2} .5189842{col 28}{space 2} .0292391{col 39}{space 1}   17.75{col 48}{space 3}0.000{col 56}{space 4} .4616105{col 69}{space 3}  .576358
{txt}{space 11}L2. {c |}{col 16}{res}{space 2}-.0397319{col 28}{space 2} .0325069{col 39}{space 1}   -1.22{col 48}{space 3}0.222{col 56}{space 4}-.1035178{col 69}{space 3} .0240541
{txt}{space 11}L3. {c |}{col 16}{res}{space 2} .0427898{col 28}{space 2} .0319004{col 39}{space 1}    1.34{col 48}{space 3}0.180{col 56}{space 4}-.0198061{col 69}{space 3} .1053856
{txt}{space 11}L4. {c |}{col 16}{res}{space 2}-.0769629{col 28}{space 2} .0280802{col 39}{space 1}   -2.74{col 48}{space 3}0.006{col 56}{space 4}-.1320626{col 69}{space 3}-.0218632
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} 24.58795{col 28}{space 2} 2.571223{col 39}{space 1}    9.56{col 48}{space 3}0.000{col 56}{space 4} 19.54263{col 69}{space 3} 29.63328
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       sigma_u {c |} {res} 19.107986
       {txt}sigma_e {c |} {res} 63.622718
           {txt}rho {c |} {res} .08273691{txt}   (fraction of variance due to u_i)
{hline 15}{c BT}{hline 64}
F test that all u_i=0:     F({res}31{txt}, {res}1049{txt}) = {res}    1.97            {txt}Prob > F = {res}0.0013
{txt}
{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1085{col 25}-6201.932{col 37}-6027.216{col 48}    5{col 57} 12064.43{col 69} 12089.38
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. predict absresid2ndpred4, xbu
{txt}(515 missing values generated)

{com}. 
. 
. 
. correlate absresid2ndpred1 absresid2ndpred2 absresid2ndpred3 absresid2ndpred4 
{txt}(obs=1085)

             {c |} a~dpred1 a~dpred2 a~dpred3 a~dpred4
{hline 13}{c +}{hline 36}
absresid2n~1 {c |}{res}   1.0000
{txt}absresid2n~2 {c |}{res}   0.9986   1.0000
{txt}absresid2n~3 {c |}{res}   0.9969   0.9985   1.0000
{txt}absresid2n~4 {c |}{res}   0.9871   0.9905   0.9902   1.0000

{txt}
{com}. 
. 
. 
. 
. * NOTE: Results of the testing process above is that we will use ARCH(1) going forward because the correlations with higher-order ARCH lag processes are > + 0.99, 
. * plus we save from unnecessarily losing observations
. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. 
. 
. gen lagabsresidstage2=l.absresidstage2
{txt}(384 missing values generated)

{com}. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. * EQUATION (2.5): "FINAL" SECOND-STAGE ARCH(1) RESIDUAL ANALYSIS *
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. bootstrap _b, reps(10003) bca seed(123) nodots saving(eq3primeboot, replace): xtreg absresidstage2 lagabsresidstage2, fe
{res}
{txt}Fixed-effects (within) regression               Number of obs      = {res}     1202
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.2387                         {txt}Obs per group: min = {res}       16
{txt}       between = {res}0.9886                                        {txt}avg = {res}     37.6
{txt}       overall = {res}0.3221                                        {txt}max = {res}       45

                                                {txt}Wald chi2({res}1{txt})       = {res}    47.67
{txt}corr(u_i, Xb)  = {res}0.3875                         {txt}Prob > chi2        =    {res}0.0000

{txt}{ralign 83:(Replications based on clustering on agencycode)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}   Observed{col 31}   Bootstrap{col 59}         Norm{col 72}al-based
{col 1}   absresidstage2{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
lagabsresidstage2 {c |}{col 19}{res}{space 2} .4725866{col 31}{space 2}  .068451{col 42}{space 1}    6.90{col 51}{space 3}0.000{col 59}{space 4} .3384251{col 72}{space 3} .6067481
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} 24.25309{col 31}{space 2} 2.656596{col 42}{space 1}    9.13{col 51}{space 3}0.000{col 59}{space 4} 19.04626{col 72}{space 3} 29.45993
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          sigma_u {c |} {res} 17.716771
          {txt}sigma_e {c |} {res} 66.737115
              {txt}rho {c |} {res} .06583515{txt}   (fraction of variance due to u_i)
{hline 18}{c BT}{hline 64}

{com}. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1202{col 25}-6902.077{col 37}-6738.148{col 48}    2{col 57}  13480.3{col 69} 13490.48
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. predict bstrapeq3p, xbu
{txt}(398 missing values generated)

{com}. 
. 
. 
. xtile bootmedcons4=_b[_cons], nquantiles(2)
{txt}
{com}. xtile bootmedlagstage2resid=_b[lagabsresidstage2], nquantiles(2)
{txt}
{com}. 
. gen cfesdhat2=bootmedcons4+bootmedlagstage2resid*lagabsresidstage2
{txt}(384 missing values generated)

{com}. 
. gen cfesd2party=cfesdhat2*presparty
{txt}(384 missing values generated)

{com}. gen cfesd2modagency=cfesdhat2*modagency
{txt}(384 missing values generated)

{com}. gen cfesd2libagency=cfesdhat2*libagency
{txt}(384 missing values generated)

{com}. gen cfesd2partymodag=cfesdhat2*modagency*presparty
{txt}(384 missing values generated)

{com}. gen cfesd2partylibag=cfesdhat2*libagency*presparty
{txt}(384 missing values generated)

{com}. 
. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. ******* EQUATION (2.6): SECOND-STAGE/"FINAL' GENERALIZED PROPOSAL EQUATION ANALYSIS & CORRESPONDING WALD-TYPE HYPOTHESIS TESTS (DERIVED FROM THE EMPIRICAL DISTRIBUTION FUNCTION VIA 10,000 BOOTSTRAP SIMULATIONS) ********
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. 
. *** "PRELIMINARY" EQUATION (2.6) ESTIMATES (SANS BOOTSTRAP STANDARD ERRORS)-- USED TO OBTAIN MODEL FIT STATISTICS (DO NOT REPORT COEFFICIENTS AND STANDARD ERRORS FROM THIS MODEL RUN)***
.  
. regress prgrowth ///
>         scpprop presparty libagency modagency partymod partylib cfesdhat2 cfesd2party cfesd2modagency cfesd2libagency ///
>         cfesd2partymodag cfesd2partylibag

      {txt}Source {c |}       SS       df       MS              Number of obs ={res}    1202
{txt}{hline 13}{char +}{hline 30}           F( 12,  1189) ={res}   18.11
    {txt}   Model {char |} {res}   382335.9    12   31861.325           {txt}Prob > F      = {res} 0.0000
    {txt}Residual {char |} {res} 2091357.87  1189  1758.92167           {txt}R-squared     = {res} 0.1546
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.1460
    {txt}   Total {char |} {res} 2473693.77  1201  2059.69506           {txt}Root MSE      = {res}  41.94

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        prgrowth{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}scpprop {c |}{col 18}{res}{space 2} .8670911{col 30}{space 2} .0647735{col 41}{space 1}   13.39{col 50}{space 3}0.000{col 58}{space 4}  .740008{col 71}{space 3} .9941741
{txt}{space 7}presparty {c |}{col 18}{res}{space 2}-.8164916{col 30}{space 2} 5.407946{col 41}{space 1}   -0.15{col 50}{space 3}0.880{col 58}{space 4}-11.42667{col 71}{space 3} 9.793688
{txt}{space 7}libagency {c |}{col 18}{res}{space 2}-2.097696{col 30}{space 2} 4.079541{col 41}{space 1}   -0.51{col 50}{space 3}0.607{col 58}{space 4} -10.1016{col 71}{space 3} 5.906206
{txt}{space 7}modagency {c |}{col 18}{res}{space 2}-1.287842{col 30}{space 2} 4.087741{col 41}{space 1}   -0.32{col 50}{space 3}0.753{col 58}{space 4}-9.307831{col 71}{space 3} 6.732146
{txt}{space 8}partymod {c |}{col 18}{res}{space 2}-6.321107{col 30}{space 2} 7.658356{col 41}{space 1}   -0.83{col 50}{space 3}0.409{col 58}{space 4} -21.3465{col 71}{space 3} 8.704289
{txt}{space 8}partylib {c |}{col 18}{res}{space 2}-1.059327{col 30}{space 2}  9.03623{col 41}{space 1}   -0.12{col 50}{space 3}0.907{col 58}{space 4}-18.78806{col 71}{space 3} 16.66941
{txt}{space 7}cfesdhat2 {c |}{col 18}{res}{space 2}-.0195877{col 30}{space 2} .0314618{col 41}{space 1}   -0.62{col 50}{space 3}0.534{col 58}{space 4}-.0813146{col 71}{space 3} .0421392
{txt}{space 5}cfesd2party {c |}{col 18}{res}{space 2} .1020585{col 30}{space 2} .0869168{col 41}{space 1}    1.17{col 50}{space 3}0.241{col 58}{space 4}-.0684688{col 71}{space 3} .2725858
{txt}{space 1}cfesd2modagency {c |}{col 18}{res}{space 2} .0020721{col 30}{space 2} .0637028{col 41}{space 1}    0.03{col 50}{space 3}0.974{col 58}{space 4}-.1229103{col 71}{space 3} .1270545
{txt}{space 1}cfesd2libagency {c |}{col 18}{res}{space 2} .1044018{col 30}{space 2} .0397157{col 41}{space 1}    2.63{col 50}{space 3}0.009{col 58}{space 4} .0264811{col 71}{space 3} .1823224
{txt}cfesd2partymodag {c |}{col 18}{res}{space 2}-.0663316{col 30}{space 2} .1069342{col 41}{space 1}   -0.62{col 50}{space 3}0.535{col 58}{space 4}-.2761324{col 71}{space 3} .1434691
{txt}cfesd2partylibag {c |}{col 18}{res}{space 2}-.1041372{col 30}{space 2} .1092783{col 41}{space 1}   -0.95{col 50}{space 3}0.341{col 58}{space 4}-.3185369{col 71}{space 3} .1102625
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0191511{col 30}{space 2} 2.481409{col 41}{space 1}    0.01{col 50}{space 3}0.994{col 58}{space 4}-4.849276{col 71}{space 3} 4.887578
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. estat ic 

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1202{col 25}-6290.882{col 37}-6189.975{col 48}   13{col 57} 12405.95{col 69} 12472.14
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. 
. 
. 
. *** "FINAL" EQUATION (2.6) ESTIMATES --  REPORT COEFFICIENTS AND STANDARD ERRORS (COEFFICIENTS AND SAMPLE SIZE SHOULD BE IDENTICAL TO "PRELIMINARY ESTIMATES" ABOVE ***
.         
. 
. xtset, clear
{txt}
{com}. 
. *eststo clear
. 
. quietly bootstrap _b, reps(10010) bca seed(123) cluster(agencycode) idcluster(new3agencycode) saving(cfesregboot, replace): regress prgrowth ///
>         scpprop presparty libagency modagency partymod partylib cfesdhat2 cfesd2party cfesd2modagency cfesd2libagency ///
>         cfesd2partymodag cfesd2partylibag
{err}xxxxxxxxxx{txt}
{com}. 
. estat bootstrap, all

{txt}Linear regression{col 49}Number of obs{col 68}= {res}     1202
{txt}{col 49}Replications{col 68}= {res}    10000

{txt}{ralign 78:(Replications based on {res:32} clusters in agencycode)}
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 11}{hline 13}{hline 12}{hline 10}{hline 6}
{col 14}{text}{c |}    Observed{col 38}    Bootstrap
{col 1}{text}    prgrowth{col 14}{c |}       Coef.{col 27}       Bias{col 38}    Std. Err.{col 51}  [95% Conf. Interval]
{col 1}{text}{hline 13}{c +}{hline 12}{hline 11}{hline 13}{hline 12}{hline 10}{hline 6}
{col 1}{text}     scpprop{col 14}{c |}{result}{space 2} .86709105{col 27}{space 2} .0542084{col 38}{space 2} .26299923{col 51}{space 2}  .351622{col 63}{space 1}  1.38256{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2} .4709492{col 63}{space 1} 1.477663{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} .4353981{col 63}{space 1} 1.417452{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .3679472{col 63}{space 1} 1.340394{col 73}{text} (BCa)
{col 1}{text}   presparty{col 14}{c |}{result}{space 2}-.81649161{col 27}{space 2} .5027596{col 38}{space 2} 5.1926712{col 51}{space 2}-10.99394{col 63}{space 1} 9.360957{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-10.21126{col 63}{space 1} 10.47374{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-11.24272{col 63}{space 1} 9.516894{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-9.920402{col 63}{space 1}  10.9615{col 73}{text} (BCa)
{col 1}{text}   libagency{col 14}{c |}{result}{space 2}-2.0976955{col 27}{space 2} .1387827{col 38}{space 2} 5.3839122{col 51}{space 2}-12.64997{col 63}{space 1} 8.454578{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2} -13.0215{col 63}{space 1} 8.460298{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-13.43587{col 63}{space 1} 8.084592{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-13.32327{col 63}{space 1} 8.199973{col 73}{text} (BCa)
{col 1}{text}   modagency{col 14}{c |}{result}{space 2}-1.2878422{col 27}{space 2}-.0052701{col 38}{space 2} 3.4819737{col 51}{space 2}-8.112385{col 63}{space 1} 5.536701{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-8.055149{col 63}{space 1} 5.754109{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-7.934506{col 63}{space 1} 5.795288{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -7.67881{col 63}{space 1} 6.068959{col 73}{text} (BCa)
{col 1}{text}    partymod{col 14}{c |}{result}{space 2}-6.3211069{col 27}{space 2}-.7625154{col 38}{space 2} 5.6393726{col 51}{space 2}-17.37407{col 63}{space 1}  4.73186{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-18.65584{col 63}{space 1} 3.692426{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-16.86856{col 63}{space 1} 5.311821{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-17.94908{col 63}{space 1}  4.26945{col 73}{text} (BCa)
{col 1}{text}    partylib{col 14}{c |}{result}{space 2}-1.0593267{col 27}{space 2}-1.849976{col 38}{space 2} 8.3200214{col 51}{space 2}-17.36627{col 63}{space 1} 15.24762{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-20.28588{col 63}{space 1} 12.94585{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-16.51775{col 63}{space 1}  17.0165{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-16.29302{col 63}{space 1} 17.43614{col 73}{text} (BCa)
{col 1}{text}   cfesdhat2{col 14}{c |}{result}{space 2}-.01958771{col 27}{space 2} .0113737{col 38}{space 2} .03911312{col 51}{space 2} -.096248{col 63}{space 1} .0570726{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0651363{col 63}{space 1} .0724233{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0935831{col 63}{space 1} .0369629{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1116448{col 63}{space 1} .0304753{col 73}{text} (BCa)
{col 1}{text} cfesd2party{col 14}{c |}{result}{space 2} .10205848{col 27}{space 2}-.0310458{col 38}{space 2} .08472157{col 51}{space 2}-.0639927{col 63}{space 1} .2681097{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1011716{col 63}{space 1} .2446275{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0177687{col 63}{space 1} .4737591{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .0027861{col 63}{space 1} .8028252{col 73}{text} (BCa)
{col 1}{text}cfesd2moda~y{col 14}{c |}{result}{space 2} .00207207{col 27}{space 2}-.0113009{col 38}{space 2} .06160462{col 51}{space 2}-.1186708{col 63}{space 1} .1228149{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1557428{col 63}{space 1}  .093054{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1330228{col 63}{space 1} .1030331{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1293851{col 63}{space 1} .1048361{col 73}{text} (BCa)
{col 1}{text}cfesd2liba~y{col 14}{c |}{result}{space 2} .10440176{col 27}{space 2}-.0211638{col 38}{space 2} .04731653{col 51}{space 2} .0116631{col 63}{space 1} .1971405{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0241713{col 63}{space 1} .1558327{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} .0354047{col 63}{space 1} .1997766{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .0404854{col 63}{space 1} .2121766{col 73}{text} (BCa)
{col 1}{text}cfesd2pa~dag{col 14}{c |}{result}{space 2}-.06633164{col 27}{space 2}  .031156{col 38}{space 2} .09773911{col 51}{space 2}-.2578968{col 63}{space 1} .1252335{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.2219448{col 63}{space 1} .1684852{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.3485071{col 63}{space 1} .1019632{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.4292148{col 63}{space 1} .0871434{col 73}{text} (BCa)
{col 1}{text}cfesd2pa~bag{col 14}{c |}{result}{space 2}-.10413721{col 27}{space 2} .0588196{col 38}{space 2} .10701861{col 51}{space 2}-.3138898{col 63}{space 1} .1056154{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.2452224{col 63}{space 1}  .178004{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} -.577034{col 63}{space 1} .0316766{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -.808752{col 63}{space 1} .0203776{col 73}{text} (BCa)
{col 1}{text}       _cons{col 14}{c |}{result}{space 2} .01915105{col 27}{space 2} -.228644{col 38}{space 2} 2.7873742{col 51}{space 2}-5.444002{col 63}{space 1} 5.482304{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-6.314542{col 63}{space 1} 4.747733{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} -6.17063{col 63}{space 1} 4.847144{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -6.99426{col 63}{space 1} 4.409815{col 73}{text} (BCa)
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 11}{hline 13}{hline 12}{hline 10}{hline 6}
{col 0}(N){col 8}normal confidence interval
{col 0}(P){col 8}percentile confidence interval
{col 0}(BC){col 8}bias-corrected confidence interval
{col 0}(BCa){col 8}bias-corrected and accelerated confidence interval
{p 0 6 0 79}Note: one or more parameters could not be estimated in 10 bootstrap replicates; standard-error estimates include only complete replications.{p_end}

{com}. 
. predict execreqgp, xb
{txt}(396 missing values generated)

{com}. 
. quietly bootstrap _b h1=(_b[_cons]) ///
>         h2=(_b[_cons] +_b[modagency]) ///
>         h3=(_b[_cons] +_b[libagency]) /// 
>         h4=(_b[libagency] - _b[modagency]) /// 
>         h5=(_b[_cons] + _b[presparty]) ///
>         h6=(_b[_cons] + _b[presparty] + _b[modagency] + _b[partymod]) /// 
>         h7=(_b[_cons] + _b[presparty] + _b[libagency] + _b[partylib]) ///
>         h8=(_b[libagency] + _b[partylib] - _b[modagency] - _b[partymod]) /// 
>         h9=(_b[cfesdhat2]) /// 
>         h10=(_b[cfesdhat2] + _b[cfesd2modagency]) ///
>         h11=(_b[cfesdhat2] + _b[cfesd2libagency]) ///
>         h12=(_b[cfesd2modagency] - _b[cfesd2libagency]) /// 
>         h13=(_b[cfesdhat2] + _b[cfesd2party]) ///
>         h14=(_b[cfesdhat2] + _b[cfesd2party] + _b[cfesd2modagency] + _b[cfesd2partymodag]) ///
>         h15=(_b[cfesdhat2] + _b[cfesd2party] + _b[cfesd2libagency] + _b[cfesd2partylibag])  ///
>         h16=(_b[cfesd2libagency] + _b[cfesd2partylibag] -  _b[cfesd2modagency] - _b[cfesd2partymodag]) h17=(_b[presparty]) ///
>         h18=(_b[presparty] + _b[partymod]) ///
>         h19=(_b[presparty] + _b[partylib]) /// 
>         h20=(_b[cfesd2party]) /// 
>         h21=(_b[cfesdhat2] + _b[cfesd2partymodag]) /// 
>         h22=(_b[cfesdhat2] + _b[cfesd2partylibag]), ///
>         cluster(agencycode) idcluster(new4agencycode) ///
>           reps(10010) bca seed(123): regress prgrowth scpprop presparty libagency modagency partymod partylib /// 
>       cfesdhat2 cfesd2party cfesd2modagency cfesd2libagency cfesd2partymodag cfesd2partylibag
{err}xxxxxxxxxx{txt}
{com}. 
. estat bootstrap, all

{txt}Linear regression{col 49}Number of obs{col 68}= {res}     1202
{txt}{col 49}Replications{col 68}= {res}    10000
{p2colset 7 17 21 2}{...}

{txt}{p2col :command:}regress prgrowth scpprop presparty libagency modagency partymod partylib cfesdhat2 cfesd2party cfesd2modagency cfesd2libagency cfesd2partymodag cfesd2partylibag{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h1:}{res:_b[_cons]}{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h2:}{res:_b[_cons] +_b[modagency]}{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h3:}{res:_b[_cons] +_b[libagency]}{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h4:}{res:_b[libagency] - _b[modagency]}{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h5:}{res:_b[_cons] + _b[presparty]}{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h6:}{res:_b[_cons] + _b[presparty] + _b[modagency] + _b[partymod]}{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h7:}{res:_b[_cons] + _b[presparty] + _b[libagency] + _b[partylib]}{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h8:}{res:_b[libagency] + _b[partylib] - _b[modagency] - _b[partymod]}{p_end}
{p2colset 6 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h9:}{res:_b[cfesdhat2]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h10:}{res:_b[cfesdhat2] + _b[cfesd2modagency]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h11:}{res:_b[cfesdhat2] + _b[cfesd2libagency]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h12:}{res:_b[cfesd2modagency] - _b[cfesd2libagency]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h13:}{res:_b[cfesdhat2] + _b[cfesd2party]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h14:}{res:_b[cfesdhat2] + _b[cfesd2party] + _b[cfesd2modagency] + _b[cfesd2partymodag]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h15:}{res:_b[cfesdhat2] + _b[cfesd2party] + _b[cfesd2libagency] + _b[cfesd2partylibag]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h16:}{res:_b[cfesd2libagency] + _b[cfesd2partylibag] - _b[cfesd2modagency] - _b[cfesd2partymodag]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h17:}{res:_b[presparty]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h18:}{res:_b[presparty] + _b[partymod]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h19:}{res:_b[presparty] + _b[partylib]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h20:}{res:_b[cfesd2party]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h21:}{res:_b[cfesdhat2] + _b[cfesd2partymodag]}{p_end}
{p2colset 5 17 21 2}{...}
{p2col :{txt}[{res:_eq2}]h22:}{res:_b[cfesdhat2] + _b[cfesd2partylibag]}{p_end}

{ralign 78:(Replications based on {res:32} clusters in agencycode)}
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 11}{hline 13}{hline 12}{hline 10}{hline 6}
{col 14}{text}{c |}    Observed{col 38}    Bootstrap
{col 14}{text}{c |}       Coef.{col 27}       Bias{col 38}    Std. Err.{col 51}  [95% Conf. Interval]
{col 1}{text}{hline 13}{c +}{hline 12}{hline 11}{hline 13}{hline 12}{hline 10}{hline 6}
{col 1}{result}_eq1        {col 14}{text}{c |}
{col 1}{text}     scpprop{col 14}{c |}{result}{space 2} .86709105{col 27}{space 2} .0542084{col 38}{space 2} .26299923{col 51}{space 2}  .351622{col 63}{space 1}  1.38256{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2} .4709492{col 63}{space 1} 1.477663{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} .4353981{col 63}{space 1} 1.417452{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .3679472{col 63}{space 1} 1.340394{col 73}{text} (BCa)
{col 1}{text}   presparty{col 14}{c |}{result}{space 2}-.81649161{col 27}{space 2} .5027596{col 38}{space 2} 5.1926712{col 51}{space 2}-10.99394{col 63}{space 1} 9.360957{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-10.21126{col 63}{space 1} 10.47374{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-11.24272{col 63}{space 1} 9.516894{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-9.920402{col 63}{space 1}  10.9615{col 73}{text} (BCa)
{col 1}{text}   libagency{col 14}{c |}{result}{space 2}-2.0976955{col 27}{space 2} .1387827{col 38}{space 2} 5.3839122{col 51}{space 2}-12.64997{col 63}{space 1} 8.454578{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2} -13.0215{col 63}{space 1} 8.460298{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-13.43587{col 63}{space 1} 8.084592{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-13.32327{col 63}{space 1} 8.199973{col 73}{text} (BCa)
{col 1}{text}   modagency{col 14}{c |}{result}{space 2}-1.2878422{col 27}{space 2}-.0052701{col 38}{space 2} 3.4819737{col 51}{space 2}-8.112385{col 63}{space 1} 5.536701{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-8.055149{col 63}{space 1} 5.754109{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-7.934506{col 63}{space 1} 5.795288{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -7.67881{col 63}{space 1} 6.068959{col 73}{text} (BCa)
{col 1}{text}    partymod{col 14}{c |}{result}{space 2}-6.3211069{col 27}{space 2}-.7625154{col 38}{space 2} 5.6393726{col 51}{space 2}-17.37407{col 63}{space 1}  4.73186{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-18.65584{col 63}{space 1} 3.692426{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-16.86856{col 63}{space 1} 5.311821{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-17.94908{col 63}{space 1}  4.26945{col 73}{text} (BCa)
{col 1}{text}    partylib{col 14}{c |}{result}{space 2}-1.0593267{col 27}{space 2}-1.849976{col 38}{space 2} 8.3200214{col 51}{space 2}-17.36627{col 63}{space 1} 15.24762{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-20.28588{col 63}{space 1} 12.94585{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-16.51775{col 63}{space 1}  17.0165{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-16.29302{col 63}{space 1} 17.43614{col 73}{text} (BCa)
{col 1}{text}   cfesdhat2{col 14}{c |}{result}{space 2}-.01958771{col 27}{space 2} .0113737{col 38}{space 2} .03911312{col 51}{space 2} -.096248{col 63}{space 1} .0570726{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0651363{col 63}{space 1} .0724233{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0935831{col 63}{space 1} .0369629{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1116448{col 63}{space 1} .0304753{col 73}{text} (BCa)
{col 1}{text} cfesd2party{col 14}{c |}{result}{space 2} .10205848{col 27}{space 2}-.0310458{col 38}{space 2} .08472157{col 51}{space 2}-.0639927{col 63}{space 1} .2681097{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1011716{col 63}{space 1} .2446275{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0177687{col 63}{space 1} .4737591{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .0027861{col 63}{space 1} .8028252{col 73}{text} (BCa)
{col 1}{text}cfesd2moda~y{col 14}{c |}{result}{space 2} .00207207{col 27}{space 2}-.0113009{col 38}{space 2} .06160462{col 51}{space 2}-.1186708{col 63}{space 1} .1228149{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1557428{col 63}{space 1}  .093054{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1330228{col 63}{space 1} .1030331{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1293851{col 63}{space 1} .1048361{col 73}{text} (BCa)
{col 1}{text}cfesd2liba~y{col 14}{c |}{result}{space 2} .10440176{col 27}{space 2}-.0211638{col 38}{space 2} .04731653{col 51}{space 2} .0116631{col 63}{space 1} .1971405{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0241713{col 63}{space 1} .1558327{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} .0354047{col 63}{space 1} .1997766{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .0404854{col 63}{space 1} .2121766{col 73}{text} (BCa)
{col 1}{text}cfesd2pa~dag{col 14}{c |}{result}{space 2}-.06633164{col 27}{space 2}  .031156{col 38}{space 2} .09773911{col 51}{space 2}-.2578968{col 63}{space 1} .1252335{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.2219448{col 63}{space 1} .1684852{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.3485071{col 63}{space 1} .1019632{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.4292148{col 63}{space 1} .0871434{col 73}{text} (BCa)
{col 1}{text}cfesd2pa~bag{col 14}{c |}{result}{space 2}-.10413721{col 27}{space 2} .0588196{col 38}{space 2} .10701861{col 51}{space 2}-.3138898{col 63}{space 1} .1056154{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.2452224{col 63}{space 1}  .178004{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} -.577034{col 63}{space 1} .0316766{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -.808752{col 63}{space 1} .0203776{col 73}{text} (BCa)
{col 1}{text}       _cons{col 14}{c |}{result}{space 2} .01915105{col 27}{space 2} -.228644{col 38}{space 2} 2.7873742{col 51}{space 2}-5.444002{col 63}{space 1} 5.482304{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-6.314542{col 63}{space 1} 4.747733{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} -6.17063{col 63}{space 1} 4.847144{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -6.99426{col 63}{space 1} 4.409815{col 73}{text} (BCa)
{col 1}{text}{hline 13}{c +}{hline 12}{hline 11}{hline 13}{hline 12}{hline 10}{hline 6}
{col 1}{result}_eq2        {col 14}{text}{c |}
{col 1}{text}          h1{col 14}{c |}{result}{space 2} .01915105{col 27}{space 2} -.228644{col 38}{space 2} 2.7873742{col 51}{space 2}-5.444002{col 63}{space 1} 5.482304{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-6.314542{col 63}{space 1} 4.747733{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} -6.17063{col 63}{space 1} 4.847144{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -6.99426{col 63}{space 1} 4.409815{col 73}{text} (BCa)
{col 1}{text}          h2{col 14}{c |}{result}{space 2}-1.2686912{col 27}{space 2}-.2339141{col 38}{space 2}  2.068769{col 51}{space 2}-5.323404{col 63}{space 1} 2.786022{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-5.997751{col 63}{space 1} 2.173196{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-5.716302{col 63}{space 1}  2.34958{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-6.030539{col 63}{space 1} 2.130207{col 73}{text} (BCa)
{col 1}{text}          h3{col 14}{c |}{result}{space 2}-2.0785445{col 27}{space 2}-.0898612{col 38}{space 2} 4.9242737{col 51}{space 2}-11.72994{col 63}{space 1} 7.572855{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-12.55386{col 63}{space 1} 7.053979{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-12.52059{col 63}{space 1} 7.082266{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-12.29036{col 63}{space 1} 7.267686{col 73}{text} (BCa)
{col 1}{text}          h4{col 14}{c |}{result}{space 2}-.80985327{col 27}{space 2} .1440528{col 38}{space 2} 5.3430618{col 51}{space 2}-11.28206{col 63}{space 1} 9.662356{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-11.68004{col 63}{space 1} 9.482317{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-12.11422{col 63}{space 1} 8.973557{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-11.84367{col 63}{space 1} 9.163725{col 73}{text} (BCa)
{col 1}{text}          h5{col 14}{c |}{result}{space 2}-.79734056{col 27}{space 2} .2741157{col 38}{space 2} 3.9132903{col 51}{space 2}-8.467249{col 63}{space 1} 6.872567{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2} -8.98062{col 63}{space 1} 7.071982{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-10.65066{col 63}{space 1} 6.208666{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-9.539441{col 63}{space 1} 6.697665{col 73}{text} (BCa)
{col 1}{text}          h6{col 14}{c |}{result}{space 2}-8.4062897{col 27}{space 2}-.4936698{col 38}{space 2} 3.1272863{col 51}{space 2}-14.53566{col 63}{space 1}-2.276921{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-15.29983{col 63}{space 1}-3.400457{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-14.39919{col 63}{space 1}-2.795736{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-15.55842{col 63}{space 1}-3.518402{col 73}{text} (BCa)
{col 1}{text}          h7{col 14}{c |}{result}{space 2}-3.9543628{col 27}{space 2}-1.437077{col 38}{space 2} 3.9106498{col 51}{space 2} -11.6191{col 63}{space 1}  3.71037{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-15.04475{col 63}{space 1} .2331415{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-12.98214{col 63}{space 1} 1.126282{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-11.08059{col 63}{space 1} 2.144559{col 73}{text} (BCa)
{col 1}{text}          h8{col 14}{c |}{result}{space 2}  4.451927{col 27}{space 2}-.9434074{col 38}{space 2} 4.8708805{col 51}{space 2}-5.094823{col 63}{space 1} 13.99868{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-7.779163{col 63}{space 1} 11.67561{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} -6.57367{col 63}{space 1} 12.33204{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-4.627982{col 63}{space 1} 14.17732{col 73}{text} (BCa)
{col 1}{text}          h9{col 14}{c |}{result}{space 2}-.01958771{col 27}{space 2} .0113737{col 38}{space 2} .03911312{col 51}{space 2} -.096248{col 63}{space 1} .0570726{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0651363{col 63}{space 1} .0724233{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0935831{col 63}{space 1} .0369629{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1116448{col 63}{space 1} .0304753{col 73}{text} (BCa)
{col 1}{text}         h10{col 14}{c |}{result}{space 2}-.01751564{col 27}{space 2} .0000728{col 38}{space 2}  .0480539{col 51}{space 2}-.1116996{col 63}{space 1} .0766683{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1257449{col 63}{space 1} .0631887{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} -.141131{col 63}{space 1} .0553088{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -.134979{col 63}{space 1} .0580728{col 73}{text} (BCa)
{col 1}{text}         h11{col 14}{c |}{result}{space 2} .08481405{col 27}{space 2}-.0097902{col 38}{space 2} .02665615{col 51}{space 2}  .032569{col 63}{space 1} .1370591{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0024753{col 63}{space 1} .1089525{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2} .0278162{col 63}{space 1} .1174828{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .0347292{col 63}{space 1} .1283797{col 73}{text} (BCa)
{col 1}{text}         h12{col 14}{c |}{result}{space 2}-.10232969{col 27}{space 2}  .009863{col 38}{space 2} .05504677{col 51}{space 2}-.2102194{col 63}{space 1}   .00556{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.2061642{col 63}{space 1} .0116854{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.2345037{col 63}{space 1}-.0096341{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.2305174{col 63}{space 1}-.0077183{col 73}{text} (BCa)
{col 1}{text}         h13{col 14}{c |}{result}{space 2} .08247077{col 27}{space 2}-.0196721{col 38}{space 2}  .0779707{col 51}{space 2} -.070349{col 63}{space 1} .2352905{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0966829{col 63}{space 1} .2263464{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0563722{col 63}{space 1} .3604831{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -.029356{col 63}{space 1} .7425771{col 73}{text} (BCa)
{col 1}{text}         h14{col 14}{c |}{result}{space 2}  .0182112{col 27}{space 2}  .000183{col 38}{space 2} .03414474{col 51}{space 2}-.0487113{col 63}{space 1} .0851337{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0543016{col 63}{space 1} .0754968{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0635517{col 63}{space 1} .0693437{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0620272{col 63}{space 1} .0699727{col 73}{text} (BCa)
{col 1}{text}         h15{col 14}{c |}{result}{space 2} .08273532{col 27}{space 2} .0179837{col 38}{space 2} .05952788{col 51}{space 2}-.0339372{col 63}{space 1} .1994078{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2} .0418951{col 63}{space 1} .2725614{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}  .042742{col 63}{space 1} .2804981{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .0341512{col 63}{space 1} .2395665{col 73}{text} (BCa)
{col 1}{text}         h16{col 14}{c |}{result}{space 2} .06452412{col 27}{space 2} .0178007{col 38}{space 2} .06682695{col 51}{space 2}-.0664543{col 63}{space 1} .1955025{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0126755{col 63}{space 1}  .254668{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0196579{col 63}{space 1} .2340486{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0322219{col 63}{space 1} .2122112{col 73}{text} (BCa)
{col 1}{text}         h17{col 14}{c |}{result}{space 2}-.81649161{col 27}{space 2} .5027596{col 38}{space 2} 5.1926712{col 51}{space 2}-10.99394{col 63}{space 1} 9.360957{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-10.21126{col 63}{space 1} 10.47374{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-11.24272{col 63}{space 1} 9.516894{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-9.920402{col 63}{space 1}  10.9615{col 73}{text} (BCa)
{col 1}{text}         h18{col 14}{c |}{result}{space 2}-7.1375985{col 27}{space 2}-.2597557{col 38}{space 2} 2.7229803{col 51}{space 2}-12.47454{col 63}{space 1}-1.800655{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-13.00142{col 63}{space 1}-2.742961{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-12.55538{col 63}{space 1}-2.568203{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-12.78995{col 63}{space 1}-2.681452{col 73}{text} (BCa)
{col 1}{text}         h19{col 14}{c |}{result}{space 2}-1.8758183{col 27}{space 2}-1.347216{col 38}{space 2} 6.5158226{col 51}{space 2} -14.6466{col 63}{space 1} 10.89496{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2} -17.8676{col 63}{space 1} 9.061318{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}  -15.005{col 63}{space 1} 11.47557{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-13.46733{col 63}{space 1} 13.54601{col 73}{text} (BCa)
{col 1}{text}         h20{col 14}{c |}{result}{space 2} .10205848{col 27}{space 2}-.0310458{col 38}{space 2} .08472157{col 51}{space 2}-.0639927{col 63}{space 1} .2681097{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.1011716{col 63}{space 1} .2446275{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.0177687{col 63}{space 1} .4737591{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} .0027861{col 63}{space 1} .8028252{col 73}{text} (BCa)
{col 1}{text}         h21{col 14}{c |}{result}{space 2}-.08591936{col 27}{space 2} .0425297{col 38}{space 2} .11710524{col 51}{space 2}-.3154414{col 63}{space 1} .1436027{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2}-.2604436{col 63}{space 1} .2094579{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.4183258{col 63}{space 1}  .090069{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2} -.459314{col 63}{space 1}  .079356{col 73}{text} (BCa)
{col 1}{text}         h22{col 14}{c |}{result}{space 2}-.12372493{col 27}{space 2} .0701933{col 38}{space 2} .12502614{col 51}{space 2}-.3687717{col 63}{space 1} .1213218{col 73}{text}   (N)
{col 14}{text}{c |}{col 51}{result}{space 2} -.280199{col 63}{space 1} .2103239{col 73}{text}   (P)
{col 14}{text}{c |}{col 51}{result}{space 2}-.5859234{col 63}{space 1} .0316544{col 73}{text}  (BC)
{col 14}{text}{c |}{col 51}{result}{space 2}-.7099254{col 63}{space 1} .0233272{col 73}{text} (BCa)
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 11}{hline 13}{hline 12}{hline 10}{hline 6}
{col 0}(N){col 8}normal confidence interval
{col 0}(P){col 8}percentile confidence interval
{col 0}(BC){col 8}bias-corrected confidence interval
{col 0}(BCa){col 8}bias-corrected and accelerated confidence interval
{p 0 6 0 79}Note: one or more parameters could not be estimated in 10 bootstrap replicates; standard-error estimates include only complete replications.{p_end}

{com}. 
. 
. 
. *capturing the values in local macros to use in calculating the asymmetric loss function
. 
. local h1 = e(exp13)
{txt}
{com}. local h2 = e(exp15) 
{txt}
{com}. local h3 = e(exp16)
{txt}
{com}. local h4 = e(exp17)
{txt}
{com}. local h5 = e(exp18)
{txt}
{com}. local h6 = e(exp19) 
{txt}
{com}. local h7 = e(exp20)
{txt}
{com}. local h8 = e(exp21)
{txt}
{com}. local h9 = e(exp22)
{txt}
{com}. local h10 = e(exp23)
{txt}
{com}. local h11 = e(exp24)
{txt}
{com}. local h12 = e(exp25)
{txt}
{com}. local h13 = e(exp26)
{txt}
{com}. local h14 = e(exp27)
{txt}
{com}. local h15 = e(exp28)
{txt}
{com}. local h16 = e(exp29)
{txt}
{com}. local h17 = e(exp30)
{txt}
{com}. local h18 = e(exp31)
{txt}
{com}. local h19 = e(exp32)
{txt}
{com}. local h20 = e(exp33)
{txt}
{com}. local h21 = e(exp34)
{txt}
{com}. local h22 = e(exp35)
{txt}
{com}. 
. *
. *
. *
. 
. 
. 
. xtset agencycode fiscalyear, yearly
{res}{txt}{col 8}panel variable:  {res}agencycode (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}fiscalyear, 1960 to 2009
{txt}{col 17}delta:  {res}1 year
{txt}
{com}. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. 
. ***** CORRELATION BETWEEN (2.1), (2.4), & (2.6) -- EXCESS FUNDING BIAS ESTIMATES, FIRST-STAGE, & SECOND-STAGE GENERALIZED PROPOSAL MODEL PREDICTED VALUES  *****
. 
. correlate predreq1 predvalstage2 execreqgp
{txt}(obs=1204)

             {c |} predreq1 predva~2 execre~p
{hline 13}{c +}{hline 27}
    predreq1 {c |}{res}   1.0000
{txt}predvalsta~2 {c |}{res}   0.3829   1.0000
   {txt}execreqgp {c |}{res}   0.9436   0.4443   1.0000

{txt}
{com}. 
. 
. ***** CORRELATION BETWEEN (2.3) and (2.5) -- FIRST-STAGE & SECOND-STAGE ARCH(1) MODEL PREDICTED VALUES  *****
. 
. correlate cfesdhat1 cfesdhat2
{txt}(obs=1216)

             {c |} cfesdh~1 cfesdh~2
{hline 13}{c +}{hline 18}
   cfesdhat1 {c |}{res}   1.0000
   {txt}cfesdhat2 {c |}{res}   0.6124   1.0000

{txt}
{com}. 
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. 
. 
. 
. * APPROPRIATIONS GROWTH MODELS *
. 
. 
. 
. 
. * CREATING IMPLICIT BUDGETARY PREFERENCE (IP) VARIABLE: (GENERALIZED PROPOSAL - STATE-CONTINGENT BUDGETARY PREFERENCE [SCP] PROPOSAL)
. 
. 
. gen ip=execreqgp-scpprop
{txt}(396 missing values generated)

{com}. 
. 
. xtset agencycode fiscalyear, yearly
{res}{txt}{col 8}panel variable:  {res}agencycode (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}fiscalyear, 1960 to 2009
{txt}{col 17}delta:  {res}1 year
{txt}
{com}. 
. 
. 
. 
. 
. * ASSESSING CORRELATIONS AMONG RELEVANT : OBSERVED PROPOSAL (OP), STATE-CONTINGENT PREFERENCE (SCP) PROPOSAL, GENERALIZED PROPOSAL (GP = STATE-CONTINGENT PREFERENCE [SCP] PROPOSAL + IMPLICIT BUDGETARY PREFERENCES [IP]), 
. * and IMPLICIT BUDGETARY PREFERENCES (IP = GP - SCP)
. 
. 
. correlate prgrowth scpprop execreqgp ip appgrowth
{txt}(obs=1195)

             {c |} prgrowth  scpprop execre~p       ip appgro~h
{hline 13}{c +}{hline 45}
    prgrowth {c |}{res}   1.0000
     {txt}scpprop {c |}{res}   0.3776   1.0000
   {txt}execreqgp {c |}{res}   0.3980   0.9476   1.0000
          {txt}ip {c |}{res}  -0.0400  -0.4097  -0.0970   1.0000
   {txt}appgrowth {c |}{res}   0.2921  -0.2799  -0.2387   0.1905   1.0000

{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. **************** FULL SPECIFICATION (ADDITIVE EXECUTIVE BUDGET COVARIATES) ******************************
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. * MODEL (3.1a): INCLUSION OF OBSERVED EXECUTIVE BUDGET PROPOSAL GROWTH & "CONTROL" COVARIATES FROM SCP MODEL (INCLUSION OF ADMINISTRATION SPECIFIC TIME-WISE FIXED EFFECT DUMMIES: KENNEDY-JOHNSON BASELINE CAPTURED IN THE INTERCEPT) *
. ************************************************************************************************************************************************************************************************************************************** 
. 
. xtreg appgrowth prgrowth hdempct sdempct congelyr cpartmajchangecorrected asct asci lagbudgetgap ueratecong lagfedsurpdefpctgdp vietiraqwardefense budget74amends grh any_supp nixonford carter reagan ghwbush clinton gwbush if ip!=., ///
>           fe vce(bootstrap, nodots bca reps(10000) seed(123))
{res}
{txt}Fixed-effects (within) regression               Number of obs      = {res}     1195
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.3650                         {txt}Obs per group: min = {res}       15
{txt}       between = {res}0.0143                                        {txt}avg = {res}     37.3
{txt}       overall = {res}0.3103                                        {txt}max = {res}       45

                                                {txt}Wald chi2({res}20{txt})      = {res}        .
{txt}corr(u_i, Xb)  = {res}-0.3845                        {txt}Prob > chi2        =    {res}     .

{txt}{ralign 89:(Replications based on {res:32} clusters in agencycode)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}   Observed{col 37}   Bootstrap{col 65}         Norm{col 78}al-based
{col 1}              appgrowth{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}prgrowth {c |}{col 25}{res}{space 2} .5873126{col 37}{space 2} .0927178{col 48}{space 1}    6.33{col 57}{space 3}0.000{col 65}{space 4}  .405589{col 78}{space 3} .7690361
{txt}{space 16}hdempct {c |}{col 25}{res}{space 2}-.3450699{col 37}{space 2} .5503955{col 48}{space 1}   -0.63{col 57}{space 3}0.531{col 65}{space 4}-1.423825{col 78}{space 3} .7336855
{txt}{space 16}sdempct {c |}{col 25}{res}{space 2} .6540488{col 37}{space 2} .5813522{col 48}{space 1}    1.13{col 57}{space 3}0.261{col 65}{space 4}-.4853805{col 78}{space 3} 1.793478
{txt}{space 15}congelyr {c |}{col 25}{res}{space 2} 6.568925{col 37}{space 2} 2.514595{col 48}{space 1}    2.61{col 57}{space 3}0.009{col 65}{space 4} 1.640409{col 78}{space 3} 11.49744
{txt}cpartmajchangecorrected {c |}{col 25}{res}{space 2} -2.66288{col 37}{space 2} 2.185731{col 48}{space 1}   -1.22{col 57}{space 3}0.223{col 65}{space 4}-6.946834{col 78}{space 3} 1.621073
{txt}{space 19}asct {c |}{col 25}{res}{space 2}-.1209475{col 37}{space 2} .5185216{col 48}{space 1}   -0.23{col 57}{space 3}0.816{col 65}{space 4}-1.137231{col 78}{space 3} .8953363
{txt}{space 19}asci {c |}{col 25}{res}{space 2}-5.505112{col 37}{space 2} 4.445782{col 48}{space 1}   -1.24{col 57}{space 3}0.216{col 65}{space 4}-14.21868{col 78}{space 3} 3.208461
{txt}{space 11}lagbudgetgap {c |}{col 25}{res}{space 2}-.6538579{col 37}{space 2} .0706108{col 48}{space 1}   -9.26{col 57}{space 3}0.000{col 65}{space 4}-.7922525{col 78}{space 3}-.5154632
{txt}{space 13}ueratecong {c |}{col 25}{res}{space 2} .9642221{col 37}{space 2} 2.579724{col 48}{space 1}    0.37{col 57}{space 3}0.709{col 65}{space 4}-4.091944{col 78}{space 3} 6.020388
{txt}{space 4}lagfedsurpdefpctgdp {c |}{col 25}{res}{space 2} 1.007763{col 37}{space 2} .9988744{col 48}{space 1}    1.01{col 57}{space 3}0.313{col 65}{space 4} -.949995{col 78}{space 3} 2.965521
{txt}{space 5}vietiraqwardefense {c |}{col 25}{res}{space 2} 5.958349{col 37}{space 2} 3.402042{col 48}{space 1}    1.75{col 57}{space 3}0.080{col 65}{space 4} -.709531{col 78}{space 3} 12.62623
{txt}{space 9}budget74amends {c |}{col 25}{res}{space 2} .2600444{col 37}{space 2} 8.515805{col 48}{space 1}    0.03{col 57}{space 3}0.976{col 65}{space 4}-16.43063{col 78}{space 3} 16.95072
{txt}{space 20}grh {c |}{col 25}{res}{space 2}-.2106418{col 37}{space 2} 4.985589{col 48}{space 1}   -0.04{col 57}{space 3}0.966{col 65}{space 4}-9.982217{col 78}{space 3} 9.560933
{txt}{space 15}any_supp {c |}{col 25}{res}{space 2} .1948148{col 37}{space 2} 4.290489{col 48}{space 1}    0.05{col 57}{space 3}0.964{col 65}{space 4}-8.214388{col 78}{space 3} 8.604018
{txt}{space 14}nixonford {c |}{col 25}{res}{space 2}  12.5811{col 37}{space 2} 6.603627{col 48}{space 1}    1.91{col 57}{space 3}0.057{col 65}{space 4}-.3617745{col 78}{space 3} 25.52397
{txt}{space 17}carter {c |}{col 25}{res}{space 2} 1.655017{col 37}{space 2} 7.926051{col 48}{space 1}    0.21{col 57}{space 3}0.835{col 65}{space 4}-13.87976{col 78}{space 3} 17.18979
{txt}{space 17}reagan {c |}{col 25}{res}{space 2} 11.31878{col 37}{space 2} 12.94023{col 48}{space 1}    0.87{col 57}{space 3}0.382{col 65}{space 4} -14.0436{col 78}{space 3} 36.68117
{txt}{space 16}ghwbush {c |}{col 25}{res}{space 2} 7.831442{col 37}{space 2} 9.056312{col 48}{space 1}    0.86{col 57}{space 3}0.387{col 65}{space 4}-9.918604{col 78}{space 3} 25.58149
{txt}{space 16}clinton {c |}{col 25}{res}{space 2} .3544484{col 37}{space 2} 10.61766{col 48}{space 1}    0.03{col 57}{space 3}0.973{col 65}{space 4}-20.45578{col 78}{space 3} 21.16468
{txt}{space 17}gwbush {c |}{col 25}{res}{space 2}  8.92374{col 37}{space 2} 9.422378{col 48}{space 1}    0.95{col 57}{space 3}0.344{col 65}{space 4}-9.543782{col 78}{space 3} 27.39126
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-24.07836{col 37}{space 2}  23.5868{col 48}{space 1}   -1.02{col 57}{space 3}0.307{col 65}{space 4}-70.30763{col 78}{space 3} 22.15092
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} 15.095687
                {txt}sigma_e {c |} {res} 42.697478
                    {txt}rho {c |} {res} .11110914{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. 
. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1195{col 25} -6426.61{col 37}-6155.246{col 48}   20{col 57} 12350.49{col 69} 12452.21
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. * MODEL (3.1b): INCLUSION OF ONLY GENERALIZED PROPOSAL (EXECREQGP) & "CONTROL" COVARIATES FROM SCP MODEL (INCLUSION OF ADMINISTRATION SPECIFIC TIME-WISE FIXED EFFECT DUMMIES: KENNEDY-JOHNSON BASELINE CAPTURED IN THE INTERCEPT) *
. ************************************************************************************************************************************************************************************************************************************** 
. 
. xtreg appgrowth execreqgp hdempct sdempct congelyr cpartmajchangecorrected asct asci lagbudgetgap ueratecong lagfedsurpdefpctgdp vietiraqwardefense budget74amends grh any_supp nixonford carter reagan ghwbush clinton gwbush if ip!=., ///
>           fe vce(bootstrap, nodots bca reps(10000) seed(123))
{res}
{txt}Fixed-effects (within) regression               Number of obs      = {res}     1196
{txt}Group variable: {res}agencycode                      {txt}Number of groups   = {res}       32

{txt}R-sq:  within  = {res}0.1670                         {txt}Obs per group: min = {res}       15
{txt}       between = {res}0.0008                                        {txt}avg = {res}     37.4
{txt}       overall = {res}0.1341                                        {txt}max = {res}       45

                                                {txt}Wald chi2({res}20{txt})      = {res}        .
{txt}corr(u_i, Xb)  = {res}-0.4217                        {txt}Prob > chi2        =    {res}     .

{txt}{ralign 89:(Replications based on {res:32} clusters in agencycode)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}   Observed{col 37}   Bootstrap{col 65}         Norm{col 78}al-based
{col 1}              appgrowth{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}execreqgp {c |}{col 25}{res}{space 2} 1.293547{col 37}{space 2} .3698718{col 48}{space 1}    3.50{col 57}{space 3}0.000{col 65}{space 4} .5686116{col 78}{space 3} 2.018482
{txt}{space 16}hdempct {c |}{col 25}{res}{space 2} .1052186{col 37}{space 2} .5736705{col 48}{space 1}    0.18{col 57}{space 3}0.854{col 65}{space 4}-1.019155{col 78}{space 3} 1.229592
{txt}{space 16}sdempct {c |}{col 25}{res}{space 2} .2230983{col 37}{space 2} .7653391{col 48}{space 1}    0.29{col 57}{space 3}0.771{col 65}{space 4}-1.276939{col 78}{space 3} 1.723135
{txt}{space 15}congelyr {c |}{col 25}{res}{space 2} 1.086908{col 37}{space 2} 2.891633{col 48}{space 1}    0.38{col 57}{space 3}0.707{col 65}{space 4}-4.580588{col 78}{space 3} 6.754404
{txt}cpartmajchangecorrected {c |}{col 25}{res}{space 2}-.7882049{col 37}{space 2} 2.831711{col 48}{space 1}   -0.28{col 57}{space 3}0.781{col 65}{space 4}-6.338256{col 78}{space 3} 4.761846
{txt}{space 19}asct {c |}{col 25}{res}{space 2}-.2974427{col 37}{space 2} .5247683{col 48}{space 1}   -0.57{col 57}{space 3}0.571{col 65}{space 4} -1.32597{col 78}{space 3} .7310844
{txt}{space 19}asci {c |}{col 25}{res}{space 2}-5.412766{col 37}{space 2} 4.038991{col 48}{space 1}   -1.34{col 57}{space 3}0.180{col 65}{space 4}-13.32904{col 78}{space 3} 2.503511
{txt}{space 11}lagbudgetgap {c |}{col 25}{res}{space 2}-.8464976{col 37}{space 2} .1765794{col 48}{space 1}   -4.79{col 57}{space 3}0.000{col 65}{space 4}-1.192587{col 78}{space 3}-.5004085
{txt}{space 13}ueratecong {c |}{col 25}{res}{space 2}-2.328505{col 37}{space 2} 2.414398{col 48}{space 1}   -0.96{col 57}{space 3}0.335{col 65}{space 4}-7.060638{col 78}{space 3} 2.403628
{txt}{space 4}lagfedsurpdefpctgdp {c |}{col 25}{res}{space 2}-1.575576{col 37}{space 2} 1.112235{col 48}{space 1}   -1.42{col 57}{space 3}0.157{col 65}{space 4}-3.755516{col 78}{space 3} .6043646
{txt}{space 5}vietiraqwardefense {c |}{col 25}{res}{space 2}  8.48458{col 37}{space 2} 4.094591{col 48}{space 1}    2.07{col 57}{space 3}0.038{col 65}{space 4} .4593288{col 78}{space 3} 16.50983
{txt}{space 9}budget74amends {c |}{col 25}{res}{space 2}-7.428747{col 37}{space 2} 11.43721{col 48}{space 1}   -0.65{col 57}{space 3}0.516{col 65}{space 4}-29.84526{col 78}{space 3} 14.98777
{txt}{space 20}grh {c |}{col 25}{res}{space 2} -1.61198{col 37}{space 2} 6.698552{col 48}{space 1}   -0.24{col 57}{space 3}0.810{col 65}{space 4} -14.7409{col 78}{space 3} 11.51694
{txt}{space 15}any_supp {c |}{col 25}{res}{space 2} 4.549162{col 37}{space 2} 4.511197{col 48}{space 1}    1.01{col 57}{space 3}0.313{col 65}{space 4}-4.292622{col 78}{space 3} 13.39095
{txt}{space 14}nixonford {c |}{col 25}{res}{space 2}  21.5257{col 37}{space 2} 8.923228{col 48}{space 1}    2.41{col 57}{space 3}0.016{col 65}{space 4} 4.036491{col 78}{space 3}  39.0149
{txt}{space 17}carter {c |}{col 25}{res}{space 2} 16.73082{col 37}{space 2}  12.5051{col 48}{space 1}    1.34{col 57}{space 3}0.181{col 65}{space 4}-7.778728{col 78}{space 3} 41.24037
{txt}{space 17}reagan {c |}{col 25}{res}{space 2} 28.72688{col 37}{space 2} 19.67586{col 48}{space 1}    1.46{col 57}{space 3}0.144{col 65}{space 4}-9.837103{col 78}{space 3} 67.29086
{txt}{space 16}ghwbush {c |}{col 25}{res}{space 2}  25.5093{col 37}{space 2} 15.35374{col 48}{space 1}    1.66{col 57}{space 3}0.097{col 65}{space 4}-4.583474{col 78}{space 3} 55.60207
{txt}{space 16}clinton {c |}{col 25}{res}{space 2} 19.18651{col 37}{space 2} 16.74291{col 48}{space 1}    1.15{col 57}{space 3}0.252{col 65}{space 4}-13.62898{col 78}{space 3} 52.00201
{txt}{space 17}gwbush {c |}{col 25}{res}{space 2} 26.56669{col 37}{space 2} 15.47811{col 48}{space 1}    1.72{col 57}{space 3}0.086{col 65}{space 4}-3.769837{col 78}{space 3} 56.90322
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-19.56168{col 37}{space 2} 27.65456{col 48}{space 1}   -0.71{col 57}{space 3}0.479{col 65}{space 4}-73.76362{col 78}{space 3} 34.64026
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} 12.464403
                {txt}sigma_e {c |} {res} 48.882039
                    {txt}rho {c |} {res} .06105015{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. 
. estat ic

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17} 1196{col 25}-6431.488{col 37}-6322.203{col 48}   20{col 57} 12684.41{col 69} 12786.14
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}

{com}. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. ************************************************************************************************************************************************************************************************************************************** 
. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************** 
. * MODEL (3.1c):  EXTERNALLY-INDUCED PREFERENCE (SCP) PROPOSAL & INTERNALLY-INDUCED BUDGETARY PREFERENCES (IP), INCLUSION OF "CONTROL" COVARIATES IN SCP MODEL: INCLUSION OF ADMINISTRATION SPECIFIC TIME-WISE FIXED EFFECT DUMMIES (KENNEDY-JOHNSON BASELINE CAPTURED IN THE INTERCEPT) *
. ************************************************************************************************************************************************************************************************************************************** 
. 
. xtreg appgrowth scpprop ip hdempct sdempct congelyr cpartmajchangecorrected asct asci lagbudgetgap ueratecong lagfedsurpdefpctgdp vietiraqwardefense budget74amends grh any_supp nixonford carter reagan ghwbush clinton gwbush, fe vce(bootstrap, nodots bca reps(10000) seed(123))
{err}{hline 2}Break{hline 2}
{txt}{search r(1):r(1);}

end of do-file

{err}{hline 2}Break{hline 2}
{txt}{search r(1):r(1);}

{com}. do "D:\Asymmetric Loss Project\New Version (2012)\Data Folder\policy priorities.unrestricted alternative EIP models.POOLED OLS.07-15-2013.do"
{txt}
{com}. * KRAUSE & COOK "POLICY PRIORITIES" (JULY 15, 2013): ALTERNATIVE MODEL 3 ANALYSIS (RESTRICTED MODEL: EXCLUDE ALL AGENCY-LEVEL AND TIME-WISE DUMMY FIXED EFFECTS IN EIP MODEL TO ASSESS ROBUSTNESS OF THE ESTIMATED PARTISAN PRESIDENTIAL BUDGETARY PREFERENCE ESTIMATES) -- REPORTED IN SUPPLEMENTARY INFORMATION DOCUMENT) 
. 
. 
. 
. * OPEN STATA OUTPUT FILE LOG
. 
. log using "D:\Asymmetric Loss Project\New Version (2012)\Data Folder\policy priorities.restricted alternative EIP models.POOLED OLS.07-15-2013.smcl", replace
{err}log file already open
{txt}{search r(604):r(604);}

end of do-file

{search r(604):r(604);}

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}D:\Asymmetric Loss Project\New Version (2012)\Data Folder\policy priorities.unrestricted reported models.pooled ols SCP model.07-15-2013.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}15 Jul 2013, 17:36:38
{txt}{.-}
{smcl}
{txt}{sf}{ul off}